In the study, a new way to apply dynamical detrended fluctuation analysis (DDFA) was developed for estimating metabolic exercise thresholds. The method was tested on heartbeat interval datasets collected in various exercise conditions, and the estimated thresholds agreed well with laboratory references. In addition, DDFA described changes in intensity in real time during unconstrained exercise. The findings show that heartbeat interval dynamics offer a reliable way to assess exercise load without laboratory measurements. The method is also applicable to consumer devices.
The doctoral dissertation of MSc Matias Kanniainen in the field of Physics titled Exercise Intensity from Dynamical Heartbeat Interval Correlations will be publicly examined at the Faculty of Engineering and Natural Sciences of Tampere University on 27 November 2026.
The Opponent will be Professor Olivier Meste from Côte d’Azur University, France. The Custos will be Professor Esa Räsänen, Faculty of Engineering and Natural Sciences